The Relationship Between Gender Identity, Economic Stressors, Social Support, Concurrent Substance Use and Suicidal Ideation

The Relationship Between Gender Identity, Economic Stressors, Social Support, Concurrent Substance Use and Suicidal Ideation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Relationship Between Gender Identity, Economic Stressors, Social Support, Concurrent Substance Use and Suicidal Ideation Sara Kelly, Sarah Donohue, Kathleen Rospenda, Kristin Moilanen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4618444/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Mar, 2025 Read the published version in Social Psychiatry and Psychiatric Epidemiology → Version 1 posted 8 You are reading this latest preprint version Abstract Purpose To examine a comprehensive list of demographic, substance use, economic, and social factors associated with suicidal ideation (SI) among middle-aged adults. Methods Cross-sectional data were obtained from a national sample of middle-aged adults between February and November 2022. The study’s final sample include 1,337 respondents who represented the adult population of persons aged 40–60 years in the United States. Bivariate and multivariate statistics were employed to identify significant factors associated with past year SI, in particular single vs. multiple instances of SI. Results Of the sample, 140 (10.4%) reported SI in the past year. Among those, more than half (60.0%, n = 84) reported SI multiple times in the past year. Multivariable logistic regression indicated that those who were a gender minority, engaged in concurrent substance use, or had financial stressors had significantly higher odds of past SI. Multinomial regression found that concurrent substance use (adjusted odds ratio [aOR] 3.17; 95% confidence interval [CI] 1.76–5.70) and having a lower standard of living than their parents/caregivers (aOR 2.99; 95% CI 1.39–6.41) predicted repeated past year SI whereas higher social support was protective against multiple SI experiences (aOR 0.65; 95% CI 0.55–0.78). Conclusion Gender minorities and those reporting concurrent substance use had the highest odds of past year SI. Findings underscore the need to develop public health and clinical interventions tailored to these highest-risk middle-aged adults in order to prevent suicide. Background Suicide and suicidality continue to be a serious public health crisis with growing mortality rates throughout the United States (US) [ 1 – 3 ]. Over the past decade, suicide mortality rates increased by 16.3% in the US, from 12.3 to 14.3 per 100,000 between 2011 and 2021 [ 4 ]. However, suicide rates are not homogenous across population subgroups. Suicide among middle-aged adults, in particular, is a growing public health problem as adults aged 35–64 years account for 46.8% of all suicides in the US and it is the eighth leading cause of death for this age group [ 4 – 5 ]. Middle-aged adults, specifically those aged 45 to 54 years old, had the highest increase in mortality rate from 2011 to 2021, with a suicide mortality rate of 12.7 in 2011 and 18.2 per 100,000 in 2021. This equates to a 43.3% increase in mortality rate, more than double the rate of change across the general population [ 4 ]. Given the growing concern over this issue in the United States, millions of dollars in funding have been distributed to suicide prevention programs [ 5 ]. However, there is no one-size fits all intervention that works [ 6 – 7 ]. Despite numerous resources allocated to reduce suicide rates, other indicators of mental health distress, such as substance use and overdose, have been on the rise as well. As outlined by Case & Deaton, growing mortality from overdose and alcohol misuse have been referred to as deaths of despair [ 8 ]. These deaths of despair are indicators of a breakdown in the social fabric of our communities [ 4 , 9 – 10 ]. While demographic and clinical characteristics are important factors that influence these mortality rates, efforts to address factors related to chronic stress, such as social disconnectedness and economic strain, are often difficult, expensive, and take time to show change. Moreover, research suggests that economic distress is not distributed equally over time; some generations experience higher levels of economic disadvantage [ 11 ]. The impact of economic changes, such as standard of living, is unclear and often underutilized in this research [ 12 – 13 ]. However, exploring associations of these chronic risk factors, such as economic stress and social disconnectedness, within suicide and suicidal ideation (SI) might help improve suicide prevention interventions. To date, research has identified a wide range of suicide risk factors across numerous domains, underscoring the complexity of addressing this public health problem [ 5 ]. Sociodemographic risk factors including being male or living in rural areas are associated with higher suicide rates 14–15]. In addition, mental health risk factors include a diagnosis of depression, anxiety, schizophrenia, or substance use disorder (SUD) [ 15 – 18 ]. Substance use, in particular the use of opioids, is also a significant risk factor for suicide attempt, especially among those with a co-occurring mental health diagnosis [ 19 – 20 ]. While other clinical factors are associated with suicide, such as suffering from non-cancer pain, additional life events are also significant risk factors connected to suicide, including adverse life events such as economic distress, legal problems, family disruption, or other types of social disconnectedness [ 17 , 18 , 21 ]. Despite the myriad of suicide risk factors that have been previously established in the literature, little is known about the impact of generational changes in financial stability in combination with other demographic, clinical, and social stressors. Such findings could provide insights to inform tailored upstream prevention efforts needed to curtail growing suicide rates, especially among known high-risk groups. The primary aim of this study is to examine sociodemographic, substance use, economic and social stressors associated with past year suicide within a representative sample of middle-aged adults in the United States. With SI being one of the strongest predictors of suicide mortality, it is essential to have a comprehensive understanding of factors associated with SI in order to help identify individuals at the highest risk before they attempt suicide [ 17 , 22 ]. A secondary aim is to identify which of these factors were associated with single or repeated SI compared to no SI in this sample, thereby expanding the literature and current evidence. Methods Study sample The study’s main goal was to compare White versus Black middle-aged adults (aged 40–60 years old). Participants were recruited using a stratified address-based sampling frame in order to identify households that included middle-aged adults (aged 40–60 years old). Using data from the 2020 American Community Survey, Census block groups were stratified by race/ethnicity (white, black), urbanicity, and educational achievement across eight demographic strata. Invitations were sent via postal mail to a total of 101,999 households sampled across the eight strata. Potential participants were randomly selected from among eligible middle-aged adults within responding households. Eligible respondents were offered $ 15 to participate and had the option to complete the survey either by mail or online. Initial surveys were completed between February and November 2022. The study’s final sample include 1,581 respondents who represented the adult population of persons aged 40–60 in the United States. Based on criteria from the American Association for Public Opinion Research, this represents a weighted response rate of 3.48% and a weighted completion rate of 58.11% [ 23 ]. After assessing for survey completion and accuracy, in particular for questions related to suicide, the study sample included 1,337 middle-aged adults. This study was approved by the institutional review board of the University of Illinois at Chicago (UIC) (protocol #2021 − 0485). Measures SI and frequency were measured with two items from the Suicide Behaviors Questionnaire-Revised (SBQ-R) [ 24 ]. The primary outcome for the present study was the presence of thoughts of killing oneself in the past year (“How often have you thought of killing yourself in the past year?”; 1 = never, 2 = rarely (1 time), 3 = sometimes (2 times), 4 = often (3–4 times), 5 = very often (5 or more times)). If respondents failed to answer the question related to SI, they were removed from the sample for this analysis. A secondary outcome, SI frequency was categorized by number of times the respondent indicating they experienced SI in the past year. SI frequency was categorized in three mutually exclusive groups: no SI, single thought of SI, and repeated thoughts of SI. We examined a comprehensive list of domains related to health and wellbeing, such as: sociodemographic, health status, and financial or social stressors. Sociodemographic characteristics included age (years), gender (cisgender male, cisgender female, transgender, non-binary, gender queer, or other gender identification), marital status (married or cohabitating, single, never married, separated, divorced, or widowed), race/ethnicity (Non-Hispanic White, Non-Hispanic Black, Hispanic or other ethnicity), educational attainment (GED or less, high school diploma, or some education post-high school), metropolitan statistical area (urban/suburban or rural), health insurance status (no health insurance, private health insurance or public health insurance). Health status included self-reported health (excellent, very good, good, fair, or poor). Perceptions of change in economic status as an indicator of economic hardship was assessed by asking “Think about whomever was mainly responsible for raising you when they were the age you are now. Do you think your own standard of living now is much better, somewhat better, about the same, somewhat worse, or much worse than theirs was?” Responses were collapsed into the following groups: better off, about the same, or worse off than their parents/caregivers. As another way to explore the impact of where the respondents live, we examined Social vulnerability index (SVI). This is a community level measure that is comprised of factors related to poverty, lack of access to transportation, and housing environment. SVI was developed by the Centers for Disease Control and Prevention (CDC) and has been found to be directly related to several health outcomes including suicide [ 25 – 27 ]. Social support was measured with a modified version of the Social Support Network Inventory (SSNI), as this tool has been validated and studies demonstrate strong psychometric properties supporting the use as a proxy for social support, which is well known to mediate service mental health issues [ 28 ]. A score representing total social support was calculated based on responses related to levels of support for life issues and stressful experiences. The SSNI captures the amount of support an individual has in relation to intimacy, practical help, emotional support and reassurance of self-worth from the most important person to the respondent in each of four categories: partner/spouse, co-worker, friend outside of work, and relative. Support in each area and from each source are assessed on a 7-point Likert-type scale ranging from 1 to 7, with lower scores representing less support and higher scores indicating higher levels of social support. Ratings are summed for each type of support and then averaged over the number of sources of support listed by a respondent, to create a total support score. Recent substance use was assessed for alcohol, marijuana, opiates, or other illicit substances. Due to small sample sizes, other substances were grouped together and included heroin, methamphetamine, crack, hallucinogens, and inhalants. Respondents who reported using these substances in the past month were further categorized depending on number of substances. Dummy coded variables were created for those who reported any substance use or concurrent substance use. Concurrent substance use was defined as using two or more substances in the past month. Statistical analysis Data for this study was analyzed using SAS v9.4 (Cary, North Carolina). Descriptive analysis for all potential predictors were completed using cross tabulations and alpha was set to 0.05 for all tests unless otherwise specified. Bivariate analyses were conducted using chi-square test of differences, for all variables in the dataset known to be linked to suicide or mental health distress (Table 1 ). Table 1 Characteristics of middle-aged adults by past year suicide ideation status Overall No suicide ideation (n = 1,197) Suicide ideation (n = 140) p-value Demographic Median IQR a Median IQR a Median IQR a Age 50 44–56 50 44–56 50 43–56 0.69 Social vulnerability index (SVI) 0.80 0.58–0.92 0.80 0.58–0.92 0.78 0.60–0.91 < 0.001* Social support network inventory score 4.75 3.67–5.71 3.75 5.77 4.07 3.00–5.00 < 0.001* N % n % n % Gender < 0.001* Cisgender male 849 63.50 756 63.16 93 66.43 Cisgender female 471 35.23 429 35.84 42 30.00 Transgender, non-binary, etc. 11 0.82 6 0.50 5 3.57 Marital Status 0.03* Single, never married, separated, divorced, widowed 727 54.38 637 53.22 90 64.29 Married or cohabitating 596 44.58 546 45.61 50 35.71 Race/ethnicity < 0.001* Non-Hispanic White 653 48.84 570 47.62 83 59.29 Non-Hispanic Black 435 32.54 405 33.83 30 21.43 Hispanic or other race 249 18.62 222 18.55 27 19.29 Household income 0.02* Under $30,000 574 42.93 498 41.60 76 54.29 $30,001 to $60,000 319 23.86 288 24.06 31 22.14 $60,000-$90,000 166 12.42 156 13.03 10 7.14 Over $90,000 239 17.88 217 18.13 22 15.71 Educational attainment 0..37 High school diploma, GED, or less 468 35.00 423 35.34 45 32.14 Some education post-high school 858 64.17 763 63.74 95 67.86 Employment status < 0.001* Not employed 491 36.72 419 35.00 72 51.43 Employed 807 60.36 739 61.74 68 48.57 Rurality 0.65 Urban/suburban 625 46.75 557 46.53 68 48.57 Rural 712 53.25 640 53.47 72 51.43 Health insurance status 0.07 No health insurance 217 16.23 200 16.71 17 12.14 Private health insurance 500 37.40 455 38.01 45 32.14 Public health insurance 483 36.13 417 34.84 66 47.14 Public and private insurance 134 10.02 122 10.19 12 8.57 Health status < 0.001* Good, very good, or excellent 968 72.40 892 74.52 76 54.29 Fair or poor 366 27.37 302 25.23 64 45.71 Change in standard of living < 0.001* Worse 227 16.98 183 15.29 44 31.43 About the same 282 21.09 264 22.06 18 12.86 Better 748 55.95 683 57.06 65 46.43 Substance use Binge drank in past year 435 32.54 388 32.41 47 33.57 0.80 Any substance use in past month 0.003* No 653 48.84 601 50.21 52 37.14 Yes 684 51.16 596 49.79 88 62.86 Concurrent use of substances in past month < 0.001* No 1,203 89.98 1,098 91.73 105 75.00 Yes 134 10.02 99 8.27 35 25.00 Type of substance use in past month Alcohol use 597 44.65 523 43.69 74 52.86 0.10 Marijuana use 183 13.69 143 11.95 40 28.57 < 0.001* Opiate use 39 2.92 29 2.42 10 7.14 0.007* Other substance use 20 1.50 15 1.25 5 3.57 0.03* a Interquartile range (IQR) * Indicates statistical significance (p < 0.05). Using multivariable logistic regression, the aORs for past year SI were calculated for sociodemographic, substance use, economic and social support variables. Multivariable logistic regression was used to provide a more direct interpretation for the relationship between the predictors and SI. A subsequent multinomial logistic regression was performed to identify factors associated with single or repeated SI compared to those with no past year SI among the study population. Assumptions were tested by assessing multicollinearity among predictors using a variance inflation factor (VIF) with a critical value greater than 10.0. Goodness of fit indices such as the Type 3 Analysis of Effects and Wald chi-square test for maximum likelihood estimates were examined for all predictors. Adjusted odds ratios (aOR) with 95% Confidence Intervals (CIs) were calculated for each of the significant predictors in the final model. Odds ratios indicate factors significantly associated with increased odds of reporting SI in the past year, adjusted for all potential confounders. Similarly, using a multinomial logistic regression model can produce aORs and corresponding 95% CIs for those significant factors associated with SI one vs. multiple times in the past year. Results Among the study sample of 1,337 middle-aged adults, 10.5% (n = 140) reported past year SI. Those who reported SI were more often cisgender male (66.4%, p < 0.001) and were single, separated, divorced, or widowed (64.3%, p = 0.03). Similarly, those who were Non-Hispanic white (p < 0.001) or with a household income under $ 30,000 (p = 0.02) more often reported SI. Those who were not employed (p < 0.001) or reported worsening standard of living compared to their parents/caregivers (p < 0.001) more often reported past year SI. Moreover, those living in areas with lower SVI scores more often reported past year SI (median = 0.78, interquartile range [IQR]: 0.60–0.91). A larger proportion of those with past year SI reported fair or poor health (p < 0.001) or reported recent substance use (p = 0.03), in particular concurrent substance use (p < 0.001). Alcohol and marijuana use were the substances most often reported by the study sample, with higher rates of use and co-use among those with past year SI. In addition, prescription opiate use including heroin use was more often reported among those with past year SI. (Table 1 ) Moreover, 60.0% (n = 84) of those with past year SI reported past year SI two or more times, or multiple SI. Table 2 shows results of a multivariable logistic regression analysis by SI status in the past year after adjusting for other confounding factors. Those who were gender minorities (e.g., transgender, non-binary, gender queer, or other gender identity) had more than 7 times the odds of SI compared to cisgender females. Those who engaged in concurrent substance use in the past month had over three times the odds of SI. Those experiencing economic stressors, such as unemployment, had nearly twice the odds of experiencing SI. Similarly, those who reported a worse standard of living than their parents/caregivers had nearly three times the odds of past year SI compared to those who did not report any change between generations. Social support, as measured by SSNI, was a significant protective factor for SI. Those with higher social support network inventory scores had lower odds of past year SI. In particular, for each point higher the respondent scored in the SSNI, they were 31% less likely to report either SI over the past year. In addition to higher levels of support, those who were Non-Hispanic Black were approximately 50% less likely to report repeated SI. Table 2 Factors associated with past year suicide ideation among middle-aged adults in the United States Variable aOR a 95% CI b Gender Cisgender male 1.47 0.96–2.26 Cisgender female Ref - Transgender, non-binary, etc. 7.06* 1.91–26.04 Race Non-Hispanic White 1.02 0.61–1.70 Non-Hispanic Black 0.52* 0.28–0.95 Hispanic or other race Ref - Change in standard of living Worse 2.62* 1.41–4.87 About the same Ref - Better 1.67 0.94–2.99 Employment status Employed Ref - Not employed 1.80* 1.21–2.68 Concurrent use No concurrent use Ref - Concurrent use 3.29* 2.02–5.36 Social support network inventory score 0.69* 0.60–0.79 a Adjusted Odds Ratio (aOR) b 95% Confidence Interval (CI) * Indicates statistical significance (p < 0.05). Table 3 shows results from a multinomial regression analysis by SI status: single ideation, multiple ideation, compared to no SI in the past year (reference group). The most significant predictor of single or multiple SI was concurrent substance use in the past month. Those who reported the use of multiple substances in the past month had more than three times the odds of SI. Those who were unemployed had roughly twice the odds of past year SI. Interestingly, those who reported a worse standard of living than their parents/caregivers had nearly 3 times the odds of multiple SI in the past year. Similar to results in Table 2 , higher scores for the SSNI were protective for both single and multiple SI among middle-aged adults. Table 3 Factors associated with single or repeated suicide ideation among middle-aged adults in the United States Single ideation Multiple ideation Variable aOR a 95% CI b aOR a 95% CI b Change in standard of living Worse 1.58 0.68–3.66 2.99* 1.39–6.41 About the same Ref - Ref - Better 1.45 0.70–3.02 1.50 0.72–3.12 Employment status Employed Ref - Ref - Not employed 2.08* 1.22–3.56 1.79* 1.10–2.93 Concurrent substance use No concurrent use Ref - Ref - Concurrent use 3.13* 1.62–6.03 3.17* 1.76–5.70 Social support network inventory score 0.75* 0.62–0.90 0.65* 0.55–0.78 a Adjusted Odds Ratio (aOR) b 95% Confidence Interval (CI) * Indicates statistical significance (p < 0.05). Discussion The findings of this cross-sectional study in a large sample of middle-aged adults document the impact of social and economic stressors and highlight disparities related to SI. These results are consistent with research on gender minorities and demonstrate the elevated risk of suicide among this often-underrepresented population [ 29 – 30 ]. These significant associations between gender identity, concurrent substance use, social support, and economic hardship in relation to suicide risk are critical when developing both public and clinical interventions. The present study adds to and extends the literature in two ways. First, to the best of our knowledge, it is the first to report data on a national sample of middle-aged adults and examine the relationship between perceived intergenerational changes in economic status and SI. Second, it is one of the first to examine the relationship between these generational changes, social support, and concurrent substance use. Although some research does suggest that those who identify as transgender or non-binary more often face mental health and substance use issues, many of these studies are among younger adults or the Veteran population [ 29 , 31 – 35 ]. One major finding of this study is the factors associated with multiple SIs within a year, which included utilization of multiple substances in the past month, unemployment, and self-perception that the participant is worse off than one’s parents or caregivers. SI that is more frequent has been associated with suicide intent in veterans and suicide attempts in adult outpatients, these factors should be particularly considered for public health interventions [ 36 – 37 ]. For example, there is evidence to suggest that SI can be decreased in individuals with substance use disorders who undergo treatment for substance use disorder [ 38 ]. More specific interventions for those at higher risk for SI should be developed and researched to determine their effectiveness. Limitations However, this study is not without limitations. First, all measures, including those for mental health, economic and social stressors, are from self-reported data. Second, the ability to assess frequency and time of concurrent substance use was limited based on survey questions. Additional research on contextual elements that influence concurrent substance use is needed. Third, this survey largely surveyed middle-aged adults who identified as Non-Hispanic White or Black, which limits the generalizability of results to other racial groups. The small sample sizes for middle-aged adults who reported being a minority group member could impact statistical power needed to detect differences and ascertain potential racial disparities that exist. In addition, future work should explore the intersection of mental health disparities by gender and race/ethnicity. Moreover, these results are based on cross-sectional data and cannot assess causality. Additional research is needed to explore the intersection of suicide and these various risk and protective factors over time among middle-aged adults. Conclusions Overall, these results suggest the need for a more comprehensive approach to improve suicide rates among middle-aged adults. In particular, improving social and economic support systems, especially among those who are a gender minority would be valuable to reduce SI. Public health interventions that reduce stigma and provide psychosocial support among those at highest risk could also result in an improvement of mental health distress. In addition, interventions that improve the sense of belonging and acceptance in the community could be another way to mitigate potential suicide risk among this population. With respect to concurrent substance use, improving access to mental health treatment and harm reduction resources could improve multiple health outcomes, including suicide. Future work should identify interventions and policies that reduce suicide risk, especially among those experiencing higher levels of social or economic distress. Declarations Acknowledgements Study sampling methodology and data collection were led by the National Opinion Research Center (NORC) at the University of Chicago. Special thanks to Dan Lawrence and Kiplin Kaldahl for their work collecting these data. Lea Cloninger provided assistance with data curation and project administration. Funding The research presented is that of the authors and does not reflect the official policy of the National Institute of Health (NIH). This work was supported by a grant from the National Institute on Alcohol Abuse and Alcoholism of the National Institute of Health (R01AA027514). Ethics Declarations This study was approved by the institutional review board of the University of Illinois at Chicago (UIC) (protocol #2021-0485). Conflicts of Interest Dr. Karnik is supported by grants from the National Institute on Drug Abuse (UG1-DA049467, UG1-DA013720, UG1-DA020024, R61-DA057629), National Center for Advancing Translational Sciences (KL2-TR002002, UL1-TR002003), and the National Institute on Deafness and Other Communication Disorders (R01-DC021301). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. All other authors do not report any conflicts of interest. Data availability: Data for participants who agreed to data sharing will be made available through the National Institute on Alcohol Abuse and Alcoholism Data Archive. Author Contribution SK: Writing-Original draft preparation, Writing – review & editing, software, formal analysis, investigation, methodology. SD: Writing-Original draft preparation, Writing – review & editing. KR: Supervision, Writing – review & editing. KM: Data curation, software, project administration, Writing – review & editing. NK: Writing – review & editing, conceptualization. JH: Writing – review & editing, project administration. TJ: Project administration, Writing – review & editing. JR: Conceptualization, Funding acquisition, supervision, Writing – review & editing. References Pathirathna ML, Nandasena HMRKG, Atapattu AMMP, Weerasekara I. Impact of the COVID-19 pandemic on suicidal attempts and death rates: A systematic review. BMC Psychiatry . 2022;22(1):506. Hedegaard H, Curtin SC, Warner M. Increase in suicide mortality in the united states, 1999–2018. . 2020. Wang J, Sumner SA, Simon TR, et al. Trends in the incidence and lethality of suicidal acts in the united states, 2006 to 2015. . 2020;77(7):684-693. Centers for Disease Control and Prevention, National Center for Health Statistics. No title. . Center for Disease Control and Prevention, (CDC). Suicide prevention resource for action: A compilation of the best available evidence. Center for Disease Control and Prevention (CDC) . 2022. Meza JI, Bath E. One size does not fit all: Making suicide prevention and interventions equitable for our increasingly diverse communities. J.Am.Acad.Child Adolesc.Psychiatry . 2021;60(2):209-212. Mann JJ, Michel CA, Auerbach RP. Improving suicide prevention through evidence-based strategies: A systematic review. Am.J.Psychiatry . 2021;178(7):611-624. Deaton A, Case A. Deaths of despair and the future of capitalism. . 2021. Stack S. Contributing factors to suicide: Political, social, cultural and economic. Prev.Med. 2021;152:106498. Marcotte DE, Hansen B. The re‐emerging suicide crisis in the US: Patterns, causes and solutions. . 2023. Glei DA, Goldman N, Weinstein M. Perception has its own reality: Subjective versus objective measures of economic distress. . 2018;44(4):695. Frankham C, Richardson T, Maguire N. Psychological factors associated with financial hardship and mental health: A systematic review. Clin.Psychol.Rev. 2020;77:101832. Kaufman JA, Salas-Hernández LK, Komro KA, Livingston MD. Effects of increased minimum wages by unemployment rate on suicide in the USA. J.Epidemiol.Community Health . 2020;74(3):219-224. Barry R, Rehm J, de Oliveira C, Gozdyra P, Kurdyak P. Rurality and risk of suicide attempts and death by suicide among people living in four english-speaking high-income countries: A systematic review and meta-analysis. . 2020;65(7):441-447. Bohnert AS, Roeder K, Ilgen MA. Unintentional overdose and suicide among substance users: A review of overlap and risk factors. Drug Alcohol Depend. 2010;110(3):183-192. Ilgen MA, Bohnert AS, Ignacio RV, et al. Psychiatric diagnoses and risk of suicide in veterans. Arch.Gen.Psychiatry . 2010;67(11):1152-1158. Favril L, Yu R, Geddes JR, Fazel S. Individual-level risk factors for suicide mortality in the general population: An umbrella review. . 2023;8(11):e868-e877. Favril L, Yu R, Uyar A, Sharpe M, Fazel S. Risk factors for suicide in adults: Systematic review and meta-analysis of psychological autopsy studies. . 2022;25(4):148-155. Devin J, Lyons S, Murphy L, O’Sullivan M, Lynn E. Factors associated with suicide in people who use drugs: A scoping review. BMC Psychiatry . 2023;23(1):655. Forray A, Yonkers KA. The collision of mental health, substance use disorder, and suicide. . 2021;137(6):1083-1090. Ilgen MA, Kleinberg F, Ignacio RV, et al. Noncancer pain conditions and risk of suicide. . 2013;70(7):692-697. Hubers A, Moaddine S, Peersmann S, et al. Suicidal ideation and subsequent completed suicide in both psychiatric and non-psychiatric populations: A meta-analysis. . 2018;27(2):186-198. AAPOR. Standard definitions: Final dispositions of case codes and outcome rates for surveys. American Association of Public Opinion Research . 2023. Osman A, Bagge CL, Gutierrez PM, Konick LC, Kopper BA, Barrios FX. The suicidal behaviors questionnaire-revised (SBQ-R): Validation with clinical and nonclinical samples. . 2001;8(4):443-454. Liu S, Morin SB, Bourand NM, et al. Social vulnerability and risk of suicide in US adults, 2016-2020. . 2023;6(4):e239995. Khan SU, Javed Z, Lone AN, et al. Social vulnerability and premature cardiovascular mortality among US counties, 2014 to 2018. . 2021;144(16):1272-1279. Aris IM, Perng W, Dabelea D, et al. Associations of neighborhood opportunity and social vulnerability with trajectories of childhood body mass index and obesity among US children. . 2022;5(12):e2247957. Flaherty JA, Gaviria FM, Pathak DS. The measurement of social support: The social support network inventory. Compr.Psychiatry . 1983;24(6):521-529. Boyer TL, Youk AO, Haas AP, et al. Suicide, homicide, and all-cause mortality among transgender and cisgender patients in the veterans health administration. . 2021;8(3):173-180. Blosnich JR, Boyer TL, Brown GR, Kauth MR, Shipherd JC. Differences in methods of suicide death among transgender and nontransgender patients in the veterans health administration, 1999–2016. Med.Care . 2021;59:S31-S35. Blosnich JR, Brown GR, Shipherd P, Jillian C, Kauth M, Piegari RI, Bossarte RM. Prevalence of gender identity disorder and suicide risk among transgender veterans utilizing veterans health administration care. Am.J.Public Health . 2013;103(10):e27-e32. Blosnich JR, Montgomery AE, Dichter ME, et al. Social determinants and military veterans’ suicide ideation and attempt: A cross-sectional analysis of electronic health record data. . 2020;35:1759-1767. Blosnich JR, Brenner LA, Bossarte RM. Population mental health among US military veterans: Results of the veterans health module of the behavioral risk factor surveillance system, 2011–2012. Ann.Epidemiol. 2016;26(8):592-596. Perez-Brumer A, Hatzenbuehler ML, Oldenburg CE, Bockting W. Individual-and structural-level risk factors for suicide attempts among transgender adults. . 2015;41(3):164-171. Gosling H, Pratt D, Montgomery H, Lea J. The relationship between minority stress factors and suicidal ideation and behaviours amongst transgender and gender non-conforming adults: A systematic review. J.Affect.Disord. 2022;303:31-51. Nichter B, Na PJ, Stanley IH, et al. Identifying factors associated with elevated suicidal intent among US military veterans. J.Psychiatr.Res. 2022;155:68-74. Rossom RC, Coleman KJ, Ahmedani BK, et al. Suicidal ideation reported on the PHQ9 and risk of suicidal behavior across age groups. J.Affect.Disord. 2017;215:77-84. Grote V, Wagner T, Riedl D, et al. Female patients show a larger reduction in suicidal ideation in inpatient addiction treatment than male patients: Results of a single-center observational study. . 2024:31-42. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 11 Mar, 2025 Read the published version in Social Psychiatry and Psychiatric Epidemiology → Version 1 posted Editorial decision: Revision requested 07 Feb, 2025 Reviews received at journal 16 Jan, 2025 Reviewers agreed at journal 26 Dec, 2024 Reviewers agreed at journal 13 Sep, 2024 Reviewers invited by journal 24 Jul, 2024 Editor assigned by journal 01 Jul, 2024 Submission checks completed at journal 27 Jun, 2024 First submitted to journal 21 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4618444","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":324693789,"identity":"9bd20375-c39b-4bea-8ac5-419b5ccf54e2","order_by":0,"name":"Sara Kelly","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYDACHgbGAw8YbOT4GRgbgFxmorQwHEhgSDOWbCBRy+HEDQfAXCK0yPccPnAgsS3N2PhGcuMHhgrrxAZCWgzOtiUAtdjImd1IbJZgOJNOhBZ+HgOwLUAtbQyMbYcJa5Hv5/8A1HI4cfMMkJZ/RGhhONvDANayQQKkpYEILQZnjhkcSDiXZixx5mGzRMKxdGPCDutJfvjgQxkwKtvTH374UGMtS9hhIMDIBmUkEKUcDP4Qr3QUjIJRMApGIAAAXzpGYLWLrDsAAAAASUVORK5CYII=","orcid":"","institution":"University of Illinois College of Medicine Peoria","correspondingAuthor":true,"prefix":"","firstName":"Sara","middleName":"","lastName":"Kelly","suffix":""},{"id":324693791,"identity":"1ad028a4-6f44-4032-98ea-e8f916236c39","order_by":1,"name":"Sarah Donohue","email":"","orcid":"","institution":"University of Illinois College of Medicine Peoria","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Donohue","suffix":""},{"id":324693792,"identity":"90afce72-6bfd-4687-b2fb-532d7ee81378","order_by":2,"name":"Kathleen Rospenda","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Kathleen","middleName":"","lastName":"Rospenda","suffix":""},{"id":324693793,"identity":"abb1af07-387b-42ad-8808-abbc97d100ab","order_by":3,"name":"Kristin Moilanen","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Kristin","middleName":"","lastName":"Moilanen","suffix":""},{"id":324693794,"identity":"df19e7dc-8532-45c5-89e0-580541a823a7","order_by":4,"name":"Niranjan Karnik","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Niranjan","middleName":"","lastName":"Karnik","suffix":""},{"id":324693795,"identity":"f59a5746-94ef-4d90-8f1e-15af76a1f8c1","order_by":5,"name":"Jesse Herron","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Jesse","middleName":"","lastName":"Herron","suffix":""},{"id":324693796,"identity":"10ea269d-fd0d-413e-9fb1-cdd2fdfd62fb","order_by":6,"name":"Timothy Johnson","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Timothy","middleName":"","lastName":"Johnson","suffix":""},{"id":324693797,"identity":"551ff3bb-7815-4f3f-9feb-57a4d3b0cd6d","order_by":7,"name":"Judy Richman","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Judy","middleName":"","lastName":"Richman","suffix":""}],"badges":[],"createdAt":"2024-06-21 16:55:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4618444/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4618444/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00127-025-02868-6","type":"published","date":"2025-03-11T15:57:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":78689749,"identity":"f140e606-0ea1-4765-8b26-70938cc4adb0","added_by":"auto","created_at":"2025-03-17 16:13:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1109607,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4618444/v1/89caeca4-e3fb-4392-adf9-765f4c0bae19.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe Relationship Between Gender Identity, Economic Stressors, Social Support, Concurrent Substance Use and Suicidal Ideation\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eSuicide and suicidality continue to be a serious public health crisis with growing mortality rates throughout the United States (US) [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Over the past decade, suicide mortality rates increased by 16.3% in the US, from 12.3 to 14.3 per 100,000 between 2011 and 2021 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, suicide rates are not homogenous across population subgroups. Suicide among middle-aged adults, in particular, is a growing public health problem as adults aged 35\u0026ndash;64 years account for 46.8% of all suicides in the US and it is the eighth leading cause of death for this age group [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Middle-aged adults, specifically those aged 45 to 54 years old, had the highest increase in mortality rate from 2011 to 2021, with a suicide mortality rate of 12.7 in 2011 and 18.2 per 100,000 in 2021. This equates to a 43.3% increase in mortality rate, more than double the rate of change across the general population [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the growing concern over this issue in the United States, millions of dollars in funding have been distributed to suicide prevention programs [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, there is no one-size fits all intervention that works [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Despite numerous resources allocated to reduce suicide rates, other indicators of mental health distress, such as substance use and overdose, have been on the rise as well. As outlined by Case \u0026amp; Deaton, growing mortality from overdose and alcohol misuse have been referred to as deaths of despair [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These deaths of despair are indicators of a breakdown in the social fabric of our communities [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. While demographic and clinical characteristics are important factors that influence these mortality rates, efforts to address factors related to chronic stress, such as social disconnectedness and economic strain, are often difficult, expensive, and take time to show change. Moreover, research suggests that economic distress is not distributed equally over time; some generations experience higher levels of economic disadvantage [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The impact of economic changes, such as standard of living, is unclear and often underutilized in this research [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, exploring associations of these chronic risk factors, such as economic stress and social disconnectedness, within suicide and suicidal ideation (SI) might help improve suicide prevention interventions.\u003c/p\u003e \u003cp\u003eTo date, research has identified a wide range of suicide risk factors across numerous domains, underscoring the complexity of addressing this public health problem [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Sociodemographic risk factors including being male or living in rural areas are associated with higher suicide rates 14\u0026ndash;15]. In addition, mental health risk factors include a diagnosis of depression, anxiety, schizophrenia, or substance use disorder (SUD) [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Substance use, in particular the use of opioids, is also a significant risk factor for suicide attempt, especially among those with a co-occurring mental health diagnosis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. While other clinical factors are associated with suicide, such as suffering from non-cancer pain, additional life events are also significant risk factors connected to suicide, including adverse life events such as economic distress, legal problems, family disruption, or other types of social disconnectedness [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the myriad of suicide risk factors that have been previously established in the literature, little is known about the impact of generational changes in financial stability in combination with other demographic, clinical, and social stressors. Such findings could provide insights to inform tailored upstream prevention efforts needed to curtail growing suicide rates, especially among known high-risk groups. The primary aim of this study is to examine sociodemographic, substance use, economic and social stressors associated with past year suicide within a representative sample of middle-aged adults in the United States. With SI being one of the strongest predictors of suicide mortality, it is essential to have a comprehensive understanding of factors associated with SI in order to help identify individuals at the highest risk before they attempt suicide [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A secondary aim is to identify which of these factors were associated with single or repeated SI compared to no SI in this sample, thereby expanding the literature and current evidence.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy sample\u003c/h2\u003e \u003cp\u003e The study\u0026rsquo;s main goal was to compare White versus Black middle-aged adults (aged 40\u0026ndash;60 years old). Participants were recruited using a stratified address-based sampling frame in order to identify households that included middle-aged adults (aged 40\u0026ndash;60 years old). Using data from the 2020 American Community Survey, Census block groups were stratified by race/ethnicity (white, black), urbanicity, and educational achievement across eight demographic strata. Invitations were sent via postal mail to a total of 101,999 households sampled across the eight strata. Potential participants were randomly selected from among eligible middle-aged adults within responding households. Eligible respondents were offered \u003cspan\u003e$\u003c/span\u003e15 to participate and had the option to complete the survey either by mail or online. Initial surveys were completed between February and November 2022. The study\u0026rsquo;s final sample include 1,581 respondents who represented the adult population of persons aged 40\u0026ndash;60 in the United States. Based on criteria from the American Association for Public Opinion Research, this represents a weighted response rate of 3.48% and a weighted completion rate of 58.11% [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. After assessing for survey completion and accuracy, in particular for questions related to suicide, the study sample included 1,337 middle-aged adults. This study was approved by the institutional review board of the University of Illinois at Chicago (UIC) (protocol #2021\u0026thinsp;\u0026minus;\u0026thinsp;0485).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cp\u003eSI and frequency were measured with two items from the Suicide Behaviors Questionnaire-Revised (SBQ-R) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The primary outcome for the present study was the presence of thoughts of killing oneself in the past year (\u0026ldquo;How often have you thought of killing yourself in the past year?\u0026rdquo;; 1\u0026thinsp;=\u0026thinsp;never, 2\u0026thinsp;=\u0026thinsp;rarely (1 time), 3\u0026thinsp;=\u0026thinsp;sometimes (2 times), 4\u0026thinsp;=\u0026thinsp;often (3\u0026ndash;4 times), 5\u0026thinsp;=\u0026thinsp;very often (5 or more times)). If respondents failed to answer the question related to SI, they were removed from the sample for this analysis. A secondary outcome, SI frequency was categorized by number of times the respondent indicating they experienced SI in the past year. SI frequency was categorized in three mutually exclusive groups: no SI, single thought of SI, and repeated thoughts of SI.\u003c/p\u003e \u003cp\u003eWe examined a comprehensive list of domains related to health and wellbeing, such as: sociodemographic, health status, and financial or social stressors. Sociodemographic characteristics included age (years), gender (cisgender male, cisgender female, transgender, non-binary, gender queer, or other gender identification), marital status (married or cohabitating, single, never married, separated, divorced, or widowed), race/ethnicity (Non-Hispanic White, Non-Hispanic Black, Hispanic or other ethnicity), educational attainment (GED or less, high school diploma, or some education post-high school), metropolitan statistical area (urban/suburban or rural), health insurance status (no health insurance, private health insurance or public health insurance). Health status included self-reported health (excellent, very good, good, fair, or poor).\u003c/p\u003e \u003cp\u003ePerceptions of change in economic status as an indicator of economic hardship was assessed by asking \u0026ldquo;Think about whomever was mainly responsible for raising you when they were the age you are now. Do you think your own standard of living now is much better, somewhat better, about the same, somewhat worse, or much worse than theirs was?\u0026rdquo; Responses were collapsed into the following groups: better off, about the same, or worse off than their parents/caregivers. As another way to explore the impact of where the respondents live, we examined Social vulnerability index (SVI). This is a community level measure that is comprised of factors related to poverty, lack of access to transportation, and housing environment. SVI was developed by the Centers for Disease Control and Prevention (CDC) and has been found to be directly related to several health outcomes including suicide [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSocial support was measured with a modified version of the Social Support Network Inventory (SSNI), as this tool has been validated and studies demonstrate strong psychometric properties supporting the use as a proxy for social support, which is well known to mediate service mental health issues [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A score representing total social support was calculated based on responses related to levels of support for life issues and stressful experiences. The SSNI captures the amount of support an individual has in relation to intimacy, practical help, emotional support and reassurance of self-worth from the most important person to the respondent in each of four categories: partner/spouse, co-worker, friend outside of work, and relative. Support in each area and from each source are assessed on a 7-point Likert-type scale ranging from 1 to 7, with lower scores representing less support and higher scores indicating higher levels of social support. Ratings are summed for each type of support and then averaged over the number of sources of support listed by a respondent, to create a total support score.\u003c/p\u003e \u003cp\u003eRecent substance use was assessed for alcohol, marijuana, opiates, or other illicit substances. Due to small sample sizes, other substances were grouped together and included heroin, methamphetamine, crack, hallucinogens, and inhalants. Respondents who reported using these substances in the past month were further categorized depending on number of substances. Dummy coded variables were created for those who reported any substance use or concurrent substance use. Concurrent substance use was defined as using two or more substances in the past month.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData for this study was analyzed using SAS v9.4 (Cary, North Carolina). Descriptive analysis for all potential predictors were completed using cross tabulations and alpha was set to 0.05 for all tests unless otherwise specified. Bivariate analyses were conducted using chi-square test of differences, for all variables in the dataset known to be linked to suicide or mental health distress (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of middle-aged adults by past year suicide ideation status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNo suicide ideation\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1,197)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eSuicide ideation\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;140)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMedian\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMedian\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eMedian\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAge\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u0026ndash;56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44\u0026ndash;56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43\u0026ndash;56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSocial vulnerability index (SVI)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.58\u0026ndash;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u0026ndash;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60\u0026ndash;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSocial support network inventory score\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.67\u0026ndash;5.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.00\u0026ndash;5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCisgender male\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCisgender female\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTransgender, non-binary, etc.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSingle, never married, separated, divorced, widowed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMarried or cohabitating\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace/ethnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNon-Hispanic White\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNon-Hispanic Black\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHispanic or other race\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUnder $30,000\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e$30,001 to $60,000\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e$60,000-$90,000\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOver $90,000\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational attainment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0..37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHigh school diploma, GED, or less\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSome education post-high school\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e67.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNot employed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEmployed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRurality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eUrban/suburban\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRural\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e51.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth insurance status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo health insurance\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePrivate health insurance\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePublic health insurance\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e47.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePublic and private insurance\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealth status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGood, very good, or excellent\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e54.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFair or poor\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChange in standard of living\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWorse\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAbout the same\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBetter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e46.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSubstance use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBinge drank in past year\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAny substance use in past month\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConcurrent use of substances in past month\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eYes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of substance use in past month\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAlcohol use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMarijuana use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOpiate use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.007*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOther substance use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003ea\u003c/sup\u003e Interquartile range (IQR)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e* Indicates statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eUsing multivariable logistic regression, the aORs for past year SI were calculated for sociodemographic, substance use, economic and social support variables. Multivariable logistic regression was used to provide a more direct interpretation for the relationship between the predictors and SI. A subsequent multinomial logistic regression was performed to identify factors associated with single or repeated SI compared to those with no past year SI among the study population.\u003c/p\u003e \u003cp\u003eAssumptions were tested by assessing multicollinearity among predictors using a variance inflation factor (VIF) with a critical value greater than 10.0. Goodness of fit indices such as the Type 3 Analysis of Effects and Wald chi-square test for maximum likelihood estimates were examined for all predictors.\u003c/p\u003e \u003cp\u003eAdjusted odds ratios (aOR) with 95% Confidence Intervals (CIs) were calculated for each of the significant predictors in the final model. Odds ratios indicate factors significantly associated with increased odds of reporting SI in the past year, adjusted for all potential confounders. Similarly, using a multinomial logistic regression model can produce aORs and corresponding 95% CIs for those significant factors associated with SI one vs. multiple times in the past year.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAmong the study sample of 1,337 middle-aged adults, 10.5% (n\u0026thinsp;=\u0026thinsp;140) reported past year SI. Those who reported SI were more often cisgender male (66.4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and were single, separated, divorced, or widowed (64.3%, p\u0026thinsp;=\u0026thinsp;0.03). Similarly, those who were Non-Hispanic white (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or with a household income under \u003cspan\u003e$\u003c/span\u003e30,000 (p\u0026thinsp;=\u0026thinsp;0.02) more often reported SI. Those who were not employed (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or reported worsening standard of living compared to their parents/caregivers (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) more often reported past year SI. Moreover, those living in areas with lower SVI scores more often reported past year SI (median\u0026thinsp;=\u0026thinsp;0.78, interquartile range [IQR]: 0.60\u0026ndash;0.91). A larger proportion of those with past year SI reported fair or poor health (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or reported recent substance use (p\u0026thinsp;=\u0026thinsp;0.03), in particular concurrent substance use (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Alcohol and marijuana use were the substances most often reported by the study sample, with higher rates of use and co-use among those with past year SI. In addition, prescription opiate use including heroin use was more often reported among those with past year SI. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) Moreover, 60.0% (n\u0026thinsp;=\u0026thinsp;84) of those with past year SI reported past year SI two or more times, or multiple SI.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows results of a multivariable logistic regression analysis by SI status in the past year after adjusting for other confounding factors. Those who were gender minorities (e.g., transgender, non-binary, gender queer, or other gender identity) had more than 7 times the odds of SI compared to cisgender females. Those who engaged in concurrent substance use in the past month had over three times the odds of SI. Those experiencing economic stressors, such as unemployment, had nearly twice the odds of experiencing SI. Similarly, those who reported a worse standard of living than their parents/caregivers had nearly three times the odds of past year SI compared to those who did not report any change between generations. Social support, as measured by SSNI, was a significant protective factor for SI. Those with higher social support network inventory scores had lower odds of past year SI. In particular, for each point higher the respondent scored in the SSNI, they were 31% less likely to report either SI over the past year. In addition to higher levels of support, those who were Non-Hispanic Black were approximately 50% less likely to report repeated SI.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with past year suicide ideation among middle-aged adults in the United States\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eaOR \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCisgender male\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u0026ndash;2.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCisgender female\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTransgender, non-binary, etc.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.06*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.91\u0026ndash;26.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNon-Hispanic White\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61\u0026ndash;1.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNon-Hispanic Black\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.52*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u0026ndash;0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHispanic or other race\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChange in standard of living\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWorse\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.62*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.41\u0026ndash;4.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAbout the same\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBetter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94\u0026ndash;2.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEmployed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNot employed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.80*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21\u0026ndash;2.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConcurrent use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo concurrent use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eConcurrent use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.29*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.02\u0026ndash;5.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial support network inventory score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.69*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60\u0026ndash;0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003ea\u003c/sup\u003e Adjusted Odds Ratio (aOR)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003csup\u003eb\u003c/sup\u003e 95% Confidence Interval (CI)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e* Indicates statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows results from a multinomial regression analysis by SI status: single ideation, multiple ideation, compared to no SI in the past year (reference group). The most significant predictor of single or multiple SI was concurrent substance use in the past month. Those who reported the use of multiple substances in the past month had more than three times the odds of SI. Those who were unemployed had roughly twice the odds of past year SI. Interestingly, those who reported a worse standard of living than their parents/caregivers had nearly 3 times the odds of multiple SI in the past year. Similar to results in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, higher scores for the SSNI were protective for both single and multiple SI among middle-aged adults.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with single or repeated suicide ideation among middle-aged adults in the United States\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSingle ideation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultiple ideation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eaOR\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eaOR\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChange in standard of living\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWorse\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68\u0026ndash;3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.99*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.39\u0026ndash;6.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAbout the same\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBetter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u0026ndash;3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.72\u0026ndash;3.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEmployed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNot employed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.08*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.22\u0026ndash;3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.79*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10\u0026ndash;2.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConcurrent substance use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNo concurrent use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eConcurrent use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.13*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.62\u0026ndash;6.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.17*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.76\u0026ndash;5.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial support network inventory score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u0026ndash;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u0026ndash;0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e Adjusted Odds Ratio (aOR)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003e 95% Confidence Interval (CI)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* Indicates statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this cross-sectional study in a large sample of middle-aged adults document the impact of social and economic stressors and highlight disparities related to SI. These results are consistent with research on gender minorities and demonstrate the elevated risk of suicide among this often-underrepresented population [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These significant associations between gender identity, concurrent substance use, social support, and economic hardship in relation to suicide risk are critical when developing both public and clinical interventions. The present study adds to and extends the literature in two ways. First, to the best of our knowledge, it is the first to report data on a national sample of middle-aged adults and examine the relationship between perceived intergenerational changes in economic status and SI. Second, it is one of the first to examine the relationship between these generational changes, social support, and concurrent substance use. Although some research does suggest that those who identify as transgender or non-binary more often face mental health and substance use issues, many of these studies are among younger adults or the Veteran population [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOne major finding of this study is the factors associated with multiple SIs within a year, which included utilization of multiple substances in the past month, unemployment, and self-perception that the participant is worse off than one\u0026rsquo;s parents or caregivers. SI that is more frequent has been associated with suicide intent in veterans and suicide attempts in adult outpatients, these factors should be particularly considered for public health interventions [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. For example, there is evidence to suggest that SI can be decreased in individuals with substance use disorders who undergo treatment for substance use disorder [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. More specific interventions for those at higher risk for SI should be developed and researched to determine their effectiveness.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eHowever, this study is not without limitations. First, all measures, including those for mental health, economic and social stressors, are from self-reported data. Second, the ability to assess frequency and time of concurrent substance use was limited based on survey questions. Additional research on contextual elements that influence concurrent substance use is needed. Third, this survey largely surveyed middle-aged adults who identified as Non-Hispanic White or Black, which limits the generalizability of results to other racial groups. The small sample sizes for middle-aged adults who reported being a minority group member could impact statistical power needed to detect differences and ascertain potential racial disparities that exist. In addition, future work should explore the intersection of mental health disparities by gender and race/ethnicity. Moreover, these results are based on cross-sectional data and cannot assess causality. Additional research is needed to explore the intersection of suicide and these various risk and protective factors over time among middle-aged adults.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOverall, these results suggest the need for a more comprehensive approach to improve suicide rates among middle-aged adults. In particular, improving social and economic support systems, especially among those who are a gender minority would be valuable to reduce SI. Public health interventions that reduce stigma and provide psychosocial support among those at highest risk could also result in an improvement of mental health distress. In addition, interventions that improve the sense of belonging and acceptance in the community could be another way to mitigate potential suicide risk among this population. With respect to concurrent substance use, improving access to mental health treatment and harm reduction resources could improve multiple health outcomes, including suicide. Future work should identify interventions and policies that reduce suicide risk, especially among those experiencing higher levels of social or economic distress.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy sampling methodology and data collection were led by the National Opinion Research Center (NORC) at the University of Chicago. Special thanks to Dan Lawrence and Kiplin Kaldahl for their work collecting these data. Lea Cloninger provided assistance with data curation and project administration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research presented is that of the authors and does not reflect the official policy of the National Institute of Health (NIH). This work was supported by a grant from the National Institute on Alcohol Abuse and Alcoholism of the National Institute of Health (R01AA027514).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics Declarations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the institutional review board of the University of Illinois at Chicago (UIC) (protocol #2021-0485).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr. Karnik is supported by grants from the National Institute on Drug Abuse (UG1-DA049467, UG1-DA013720, UG1-DA020024, R61-DA057629), National Center for Advancing Translational Sciences (KL2-TR002002, UL1-TR002003), and the National Institute on Deafness and Other Communication Disorders (R01-DC021301). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. All other authors do not report any conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData for participants who agreed to data sharing will be made available through the National Institute on Alcohol Abuse and Alcoholism Data Archive.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSK: Writing-Original draft preparation, Writing \u0026ndash; review \u0026amp; editing, software, formal analysis, investigation, methodology. SD: Writing-Original draft preparation, Writing \u0026ndash; review \u0026amp; editing. KR: Supervision, Writing \u0026ndash; review \u0026amp; editing. KM: Data curation, software, project administration, Writing \u0026ndash; review \u0026amp; editing. NK: Writing \u0026ndash; review \u0026amp; editing, conceptualization. JH: Writing \u0026ndash; review \u0026amp; editing, project administration. TJ: Project administration, Writing \u0026ndash; review \u0026amp; editing. JR: Conceptualization, Funding acquisition, supervision, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePathirathna ML, Nandasena HMRKG, Atapattu AMMP, Weerasekara I. Impact of the COVID-19 pandemic on suicidal attempts and death rates: A systematic review. \u003cem\u003eBMC Psychiatry\u003c/em\u003e. 2022;22(1):506.\u003c/li\u003e\n\u003cli\u003eHedegaard H, Curtin SC, Warner M. Increase in suicide mortality in the united states, 1999\u0026ndash;2018. . 2020.\u003c/li\u003e\n\u003cli\u003eWang J, Sumner SA, Simon TR, et al. Trends in the incidence and lethality of suicidal acts in the united states, 2006 to 2015. . 2020;77(7):684-693.\u003c/li\u003e\n\u003cli\u003eCenters for Disease Control and Prevention, National Center for Health Statistics. No title. . \u003c/li\u003e\n\u003cli\u003eCenter for Disease Control and Prevention, (CDC). Suicide prevention resource for action: A\u003cbr\u003ecompilation of the best available evidence. \u003cem\u003eCenter for Disease Control and Prevention (CDC)\u003c/em\u003e. 2022.\u003c/li\u003e\n\u003cli\u003eMeza JI, Bath E. One size does not fit all: Making suicide prevention and interventions equitable for our increasingly diverse communities. \u003cem\u003eJ.Am.Acad.Child Adolesc.Psychiatry\u003c/em\u003e. 2021;60(2):209-212.\u003c/li\u003e\n\u003cli\u003eMann JJ, Michel CA, Auerbach RP. Improving suicide prevention through evidence-based strategies: A systematic review. \u003cem\u003eAm.J.Psychiatry\u003c/em\u003e. 2021;178(7):611-624.\u003c/li\u003e\n\u003cli\u003eDeaton A, Case A. Deaths of despair and the future of capitalism. . 2021.\u003c/li\u003e\n\u003cli\u003eStack S. Contributing factors to suicide: Political, social, cultural and economic. \u003cem\u003ePrev.Med.\u003c/em\u003e 2021;152:106498.\u003c/li\u003e\n\u003cli\u003eMarcotte DE, Hansen B. The re‐emerging suicide crisis in the US: Patterns, causes and solutions. . 2023.\u003c/li\u003e\n\u003cli\u003eGlei DA, Goldman N, Weinstein M. Perception has its own reality: Subjective versus objective measures of economic distress. . 2018;44(4):695.\u003c/li\u003e\n\u003cli\u003eFrankham C, Richardson T, Maguire N. Psychological factors associated with financial hardship and mental health: A systematic review. \u003cem\u003eClin.Psychol.Rev.\u003c/em\u003e 2020;77:101832.\u003c/li\u003e\n\u003cli\u003eKaufman JA, Salas-Hern\u0026aacute;ndez LK, Komro KA, Livingston MD. Effects of increased minimum wages by unemployment rate on suicide in the USA. \u003cem\u003eJ.Epidemiol.Community Health\u003c/em\u003e. 2020;74(3):219-224.\u003c/li\u003e\n\u003cli\u003eBarry R, Rehm J, de Oliveira C, Gozdyra P, Kurdyak P. Rurality and risk of suicide attempts and death by suicide among people living in four english-speaking high-income countries: A systematic review and meta-analysis. . 2020;65(7):441-447.\u003c/li\u003e\n\u003cli\u003eBohnert AS, Roeder K, Ilgen MA. Unintentional overdose and suicide among substance users: A review of overlap and risk factors. \u003cem\u003eDrug Alcohol Depend.\u003c/em\u003e 2010;110(3):183-192.\u003c/li\u003e\n\u003cli\u003eIlgen MA, Bohnert AS, Ignacio RV, et al. Psychiatric diagnoses and risk of suicide in veterans. \u003cem\u003eArch.Gen.Psychiatry\u003c/em\u003e. 2010;67(11):1152-1158.\u003c/li\u003e\n\u003cli\u003eFavril L, Yu R, Geddes JR, Fazel S. Individual-level risk factors for suicide mortality in the general population: An umbrella review. . 2023;8(11):e868-e877.\u003c/li\u003e\n\u003cli\u003eFavril L, Yu R, Uyar A, Sharpe M, Fazel S. Risk factors for suicide in adults: Systematic review and meta-analysis of psychological autopsy studies. . 2022;25(4):148-155.\u003c/li\u003e\n\u003cli\u003eDevin J, Lyons S, Murphy L, O\u0026rsquo;Sullivan M, Lynn E. Factors associated with suicide in people who use drugs: A scoping review. \u003cem\u003eBMC Psychiatry\u003c/em\u003e. 2023;23(1):655.\u003c/li\u003e\n\u003cli\u003eForray A, Yonkers KA. The collision of mental health, substance use disorder, and suicide. . 2021;137(6):1083-1090.\u003c/li\u003e\n\u003cli\u003eIlgen MA, Kleinberg F, Ignacio RV, et al. Noncancer pain conditions and risk of suicide. . 2013;70(7):692-697.\u003c/li\u003e\n\u003cli\u003eHubers A, Moaddine S, Peersmann S, et al. Suicidal ideation and subsequent completed suicide in both psychiatric and non-psychiatric populations: A meta-analysis. . 2018;27(2):186-198.\u003c/li\u003e\n\u003cli\u003eAAPOR. Standard definitions: Final dispositions of case codes and outcome rates for surveys. \u003cem\u003eAmerican Association of Public Opinion Research\u003c/em\u003e. 2023.\u003c/li\u003e\n\u003cli\u003eOsman A, Bagge CL, Gutierrez PM, Konick LC, Kopper BA, Barrios FX. The suicidal behaviors questionnaire-revised (SBQ-R): Validation with clinical and nonclinical samples. . 2001;8(4):443-454.\u003c/li\u003e\n\u003cli\u003eLiu S, Morin SB, Bourand NM, et al. Social vulnerability and risk of suicide in US adults, 2016-2020. . 2023;6(4):e239995.\u003c/li\u003e\n\u003cli\u003eKhan SU, Javed Z, Lone AN, et al. Social vulnerability and premature cardiovascular mortality among US counties, 2014 to 2018. . 2021;144(16):1272-1279.\u003c/li\u003e\n\u003cli\u003eAris IM, Perng W, Dabelea D, et al. Associations of neighborhood opportunity and social vulnerability with trajectories of childhood body mass index and obesity among US children. . 2022;5(12):e2247957.\u003c/li\u003e\n\u003cli\u003eFlaherty JA, Gaviria FM, Pathak DS. The measurement of social support: The social support network inventory. \u003cem\u003eCompr.Psychiatry\u003c/em\u003e. 1983;24(6):521-529.\u003c/li\u003e\n\u003cli\u003eBoyer TL, Youk AO, Haas AP, et al. Suicide, homicide, and all-cause mortality among transgender and cisgender patients in the veterans health administration. . 2021;8(3):173-180.\u003c/li\u003e\n\u003cli\u003eBlosnich JR, Boyer TL, Brown GR, Kauth MR, Shipherd JC. Differences in methods of suicide death among transgender and nontransgender patients in the veterans health administration, 1999\u0026ndash;2016. \u003cem\u003eMed.Care\u003c/em\u003e. 2021;59:S31-S35.\u003c/li\u003e\n\u003cli\u003eBlosnich JR, Brown GR, Shipherd P, Jillian C, Kauth M, Piegari RI, Bossarte RM. Prevalence of gender identity disorder and suicide risk among transgender veterans utilizing veterans health administration care. \u003cem\u003eAm.J.Public Health\u003c/em\u003e. 2013;103(10):e27-e32.\u003c/li\u003e\n\u003cli\u003eBlosnich JR, Montgomery AE, Dichter ME, et al. Social determinants and military veterans\u0026rsquo; suicide ideation and attempt: A cross-sectional analysis of electronic health record data. . 2020;35:1759-1767.\u003c/li\u003e\n\u003cli\u003eBlosnich JR, Brenner LA, Bossarte RM. Population mental health among US military veterans: Results of the veterans health module of the behavioral risk factor surveillance system, 2011\u0026ndash;2012. \u003cem\u003eAnn.Epidemiol.\u003c/em\u003e 2016;26(8):592-596.\u003c/li\u003e\n\u003cli\u003ePerez-Brumer A, Hatzenbuehler ML, Oldenburg CE, Bockting W. Individual-and structural-level risk factors for suicide attempts among transgender adults. . 2015;41(3):164-171.\u003c/li\u003e\n\u003cli\u003eGosling H, Pratt D, Montgomery H, Lea J. The relationship between minority stress factors and suicidal ideation and behaviours amongst transgender and gender non-conforming adults: A systematic review. \u003cem\u003eJ.Affect.Disord.\u003c/em\u003e 2022;303:31-51.\u003c/li\u003e\n\u003cli\u003eNichter B, Na PJ, Stanley IH, et al. Identifying factors associated with elevated suicidal intent among US military veterans. \u003cem\u003eJ.Psychiatr.Res.\u003c/em\u003e 2022;155:68-74.\u003c/li\u003e\n\u003cli\u003eRossom RC, Coleman KJ, Ahmedani BK, et al. Suicidal ideation reported on the PHQ9 and risk of suicidal behavior across age groups. \u003cem\u003eJ.Affect.Disord.\u003c/em\u003e 2017;215:77-84.\u003c/li\u003e\n\u003cli\u003eGrote V, Wagner T, Riedl D, et al. Female patients show a larger reduction in suicidal ideation in inpatient addiction treatment than male patients: Results of a single-center observational study. . 2024:31-42.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"social-psychiatry-and-psychiatric-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sppe","sideBox":"Learn more about [Social Psychiatry and Psychiatric Epidemiology](http://link.springer.com/journal/127)","snPcode":"127","submissionUrl":"https://submission.nature.com/new-submission/127/3","title":"Social Psychiatry and Psychiatric Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4618444/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4618444/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eTo examine a comprehensive list of demographic, substance use, economic, and social factors associated with suicidal ideation (SI) among middle-aged adults.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eCross-sectional data were obtained from a national sample of middle-aged adults between February and November 2022. The study\u0026rsquo;s final sample include 1,337 respondents who represented the adult population of persons aged 40\u0026ndash;60 years in the United States. Bivariate and multivariate statistics were employed to identify significant factors associated with past year SI, in particular single vs. multiple instances of SI.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the sample, 140 (10.4%) reported SI in the past year. Among those, more than half (60.0%, n\u0026thinsp;=\u0026thinsp;84) reported SI multiple times in the past year. Multivariable logistic regression indicated that those who were a gender minority, engaged in concurrent substance use, or had financial stressors had significantly higher odds of past SI. Multinomial regression found that concurrent substance use (adjusted odds ratio [aOR] 3.17; 95% confidence interval [CI] 1.76\u0026ndash;5.70) and having a lower standard of living than their parents/caregivers (aOR 2.99; 95% CI 1.39\u0026ndash;6.41) predicted repeated past year SI whereas higher social support was protective against multiple SI experiences (aOR 0.65; 95% CI 0.55\u0026ndash;0.78).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eGender minorities and those reporting concurrent substance use had the highest odds of past year SI. Findings underscore the need to develop public health and clinical interventions tailored to these highest-risk middle-aged adults in order to prevent suicide.\u003c/p\u003e","manuscriptTitle":"The Relationship Between Gender Identity, Economic Stressors, Social Support, Concurrent Substance Use and Suicidal Ideation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-19 12:22:52","doi":"10.21203/rs.3.rs-4618444/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-07T14:01:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-16T05:45:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"264829779485955167762965374883711299083","date":"2024-12-26T12:37:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120482999094311996992111410208299918366","date":"2024-09-13T13:59:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-24T16:59:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-01T11:43:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-27T08:21:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"Social Psychiatry and Psychiatric Epidemiology","date":"2024-06-21T16:14:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"social-psychiatry-and-psychiatric-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sppe","sideBox":"Learn more about [Social Psychiatry and Psychiatric Epidemiology](http://link.springer.com/journal/127)","snPcode":"127","submissionUrl":"https://submission.nature.com/new-submission/127/3","title":"Social Psychiatry and Psychiatric Epidemiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8e9c8cd1-9f0b-4159-b382-180a04ff70d4","owner":[],"postedDate":"July 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-17T16:08:56+00:00","versionOfRecord":{"articleIdentity":"rs-4618444","link":"https://doi.org/10.1007/s00127-025-02868-6","journal":{"identity":"social-psychiatry-and-psychiatric-epidemiology","isVorOnly":false,"title":"Social Psychiatry and Psychiatric Epidemiology"},"publishedOn":"2025-03-11 15:57:33","publishedOnDateReadable":"March 11th, 2025"},"versionCreatedAt":"2024-07-19 12:22:52","video":"","vorDoi":"10.1007/s00127-025-02868-6","vorDoiUrl":"https://doi.org/10.1007/s00127-025-02868-6","workflowStages":[]},"version":"v1","identity":"rs-4618444","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4618444","identity":"rs-4618444","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}